RETRACTED: Parametric sensitivity analysis of PEM fuel cell electrochemical Model

Srinivasulu, G. Naga; Subrahmanyam, T.; Rao, V. Dharma

doi:10.1016/j.ijhydene.2011.03.040

Cited by 40 publications

(13 citation statements)

References 11 publications

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“…The second case study for PEMFC is a dataset from a 500‐W fuel stack comprising of 48 single fuel cells connected in series manufactured by M/S Avista, operating under a temperature of 313 K and partial pressures of hydrogen

((), P_{H_{2}})

and oxygen

((), P_{O_{2}})

having values of 1.5 and 1 atm, respectively . The third case study for PEMFC modelling is also a dataset of a 500‐W fuel stack comprising of 32 single fuel cells connected in series manufactured by M/S BCS Technologies, operating under a temperature of 333 K and partial pressures of hydrogen

((), P_{H_{2}})

and oxygen

((), P_{O_{2}})

of 1 and 0.2075 atm, respectively . For SOFC, first case study is a single cell electrolyte supported solid oxide fuel cell (ES‐SOFC) manufactured by M/S IEn OC CEREL made of 0.09‐mm thick TOSOH Zirconia electrolyte, operating under a temperature of 1193 K .…”

Section: Pemfc/sofc Parameter Identification: Results and Discussionmentioning

confidence: 99%

“…For SOFC, first case study is a single cell electrolyte supported solid oxide fuel cell (ES‐SOFC) manufactured by M/S IEn OC CEREL made of 0.09‐mm thick TOSOH Zirconia electrolyte, operating under a temperature of 1193 K . The second case study is also a single cell ES‐SOFC manufactured by M/S Energy Research Centre of the Netherlands (ECN) made of 0.15‐mm thick TZ3Y electrolyte, operating under a temperature of 1193 K . Finally, third case study for SOFC is based on a 5‐kW fuel stack comprising of 96 single fuel cells connected in series and validated as a MATLAB®/Simulink model developed by Montana State University, operating under 1173 K …”

Section: Pemfc/sofc Parameter Identification: Results and Discussionmentioning

confidence: 99%

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Parameter extraction of fuel cells using hybrid interior search algorithm

2019

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Summary Precise modelling of fuel cells is very important for understanding their functioning. In this work, an application of hybrid interior search algorithm (HISA) is proposed to extract the parameters of fuel cells for their electromechanical equations based on nonlinear current‐voltage characteristics. Proposed hybridised algorithm has been developed using evolutionary mutation and crossover operators so as to enhance the modelling capability of interior search algorithm (ISA). To assess the modelling performance of HISA, parameter extraction of two types of fuel cell models, namely, proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) have been considered. Modelling performance of HISA, assessed using mean squared error between computed and experimental data, is found to be superior to ISA and several other recently reported prominent optimisation methods. Based on the presented intensive simulation investigations, it is concluded that HISA improves the performance of the basic ISA in terms of fitter solutions, robustness, and convergence rate and therefore offers a promising optimisation technique for parameter extraction of fuel cells.

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((), P_{H_{2}})

and oxygen

((), P_{O_{2}})

((), P_{H_{2}})

and oxygen

((), P_{O_{2}})

Section: Pemfc/sofc Parameter Identification: Results and Discussionmentioning

confidence: 99%

Section: Pemfc/sofc Parameter Identification: Results and Discussionmentioning

confidence: 99%

Parameter extraction of fuel cells using hybrid interior search algorithm

2019

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“…A rational method for selecting appropriate parameters for calibration is the parameter sensitivity analysis. Sensitivity studies have been widely reported for the polymer electrolyte membrane fuel cells using the Sobols sensitivity analysis method, the multiparametric sensitivity analysis method, and the global sensitivity analysis method . A few sensitivity analyses for the SOFC are also reported by using the discrete adjoint method and the multiparametric sensitivity analysis method .…”

Section: Introductionmentioning

confidence: 99%

Statistical method‐based calibration and validation of a solid oxide fuel cell model

2018

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Summary A 2‐stage model validation strategy for the previously developed solid oxide fuel cell model using the data from custom‐designed experiments is presented. The strategy is based on the identification of model structural and parametric errors. In the preliminary validation, the causes that can result in the voltage error during changing temperature and fuel flow rate conditions are analysed. It is identified that the convection heat transfer process contributes significantly towards the cell performance in a temperature controlled test environment. Rectification of this error results in the reduction of the maximum voltage error from 14% to 0.5%. Graphical methods for data visualisation are utilised to examine goodness of fit of the model. Input sensitivity analysis reveals that the air flow rate has negligible influence on the output quantities of current density, fuel utilisation, and cell temperature owing to temperature‐controlled conditions of the test. Parameter sensitivity analysis through the elementary effects method reveals that most of the electrochemical parameters in general and the activation energies in particular have dominant effects on the considered system outputs. Model validation is carried out through a classical statistical method of hypothesis testing by using the parameter uncertainty information obtained through nonlinear least squares fitting. The efficacy of the model validation strategy is demonstrated through the model acceptance with 8% maximum error in cell current.

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“…Typical voltage and current values range from 0.4 to 0.9V and from 0.5 to 1.0 A/cm 2 respectively after losses [8]. As shown in Figure 1, in order for fuel cells to produce high voltages, a stack is made up by connecting a number of fuel cells in series, separated by bipolar plates [9]. The different fuel cells are categorised according to the type of electrolyte they use.…”

Section: Introductionmentioning

confidence: 99%

A Review of Computational Fluid Dynamics Simulations on PEFC Performance

Chen¹,

Enearu²,

Montalvão³

et al. 2016

J Appl Mech Eng

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Among the number of fuel cells in existence, the proton exchange fuel cell (PEFC) has been favoured because of its numerous applications. These applications range from small power generation in cell phones, to stationary power plants or vehicular applications. However, the principle of operation on PEFCs naturally leads to the development of water from the reaction between hydrogen and oxygen. Computational fluid dynamics (CFD) has played an important role in many research and development projects. From automotive to aerospace and even medicine, to the development of fuel cells, by making it possible to investigate different scenarios and fluid flow patterns for optimal performance. CFD allows for in-situ analysis of PEFCs, by studying fluid flow and heat and mass transfer phenomena, thus reducing the need for expensive prototypes and cutting down test-time by a substantial amount. This paper aims at investigating the advances made in the use of CFD as a technique for the performance and optimisation of PEFCs to identify the research and development opportunities in the field, such as the performance of a novel PEFC, with focus on the underlying physics and in-situ analysis of the operations.

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RETRACTED: Parametric sensitivity analysis of PEM fuel cell electrochemical Model

Cited by 40 publications

References 11 publications

Parameter extraction of fuel cells using hybrid interior search algorithm

Parameter extraction of fuel cells using hybrid interior search algorithm

Statistical method‐based calibration and validation of a solid oxide fuel cell model

A Review of Computational Fluid Dynamics Simulations on PEFC Performance

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